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| Considering the problem of robot uncalibrated visual servoing based on an image Jacobian matrix, a novel on-line estimation of image Jacobian matrix method based on the square-root unscented Kalman filter is proposed. In this method, a state vector is formed from the elements of a total image Jacobian matrix, and the problem is converted into one of system state estimations, then a square-root unscented Kalman filter suitable for nonlinear systems is utilized for estimation of system state, thus the on-line estimation of total image Jacobian matrix is realized and the complex system calibration process can be avoided. The proposed method and the ones based on Kalman filter and unscented Kalman filter are tested to track a moving target on a two degree-of-freedom robot visual servoing system. Simulation results indicate that, the proposed method outperforms other two in estimation accuracy and robustness. |
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| Keywords:robot; uncalibrated visual servoing; image Jacobian matrix; square-root unscented Kalman filter |
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